graph_tool.dynamics

This module contains implementations of some often-studied dynamical processes that take place on networks.

Discrete-time dynamics

DiscreteStateBase	Base state for discrete-time dynamics.
EpidemicStateBase	Base state for epidemic dynamics.
SIState	SI compartmental epidemic model.
SISState	SIS compartmental epidemic model.
SIRState	SIR compartmental epidemic model.
SIRSState	SIRS compartmental epidemic model.
VoterState	Generalized q-state voter model dynamics.
MajorityVoterState	Generalized q-state majority voter model dynamics.
BinaryThresholdState	Generalized binary threshold dynamics.
IsingGlauberState	Glauber dynamics of the Ising model.
CIsingGlauberState	Glauber dynamics of the continuous Ising model.
IsingMetropolisState	Metropolis-Hastings dynamics of the Ising model.
PottsGlauberState	Glauber dynamics of the Potts model.
PottsMetropolisState	Metropolis-Hastings dynamics of the Potts model.
AxelrodState	Axelrod's culture dissemination model.
BooleanState	Boolean network dynamics.
KirmanState	Kirman's "ant colony" model.
NormalState	Multivariate Normal distribution.
LinearNormalState	Linear distrecte-time dynamical system with noise.

Continuous-time dynamics

ContinuousStateBase	Base state for continuous-time dynamics.
LinearState	Linear dynamical system with noise.
LVState	Generalized Lotka-Volterra model.
KuramotoState	The Kuramoto model.

Belief propagation

BPBaseState	Base class for belief propagation (BP) states.
GenPottsBPState	Belief-propagtion equations for a genralized Potts model.
IsingBPState	Belief-propagation equations for the Ising model.
NormalBPState	Belief-propagation equations for the multivariate Normal distribution.

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